Dynamic lot sizing problems with stochastic production output

Dynamic lot sizing problems with stochastic production output PDF Author: Michael Kirste
Publisher: BoD – Books on Demand
ISBN: 3744838056
Category : Business & Economics
Languages : en
Pages : 250

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Book Description
In the real world, production systems are affected by external and internal uncertainties. Stochastic demand - an external uncertainty - arises mainly due to forecast errors and unknown behavior of customers in future. Internal uncertainties occur in situations where random yield, random production capacity, or stochastic processing times affect the productivity of a manufacturing system. The resulting stochastic production output is especially present in industries with modern and complex technologies as the semiconductor industry. This thesis provides model formulations and solution methods for capacitated dynamic lot sizing problems with stochastic demand and stochastic production output that can be used by practitioners within Manufacturing Resource Planning Systems (MRP), Capacitated Production Planning Systems (CPPS), and Advanced Planning Systems (APS). In all models, backordered demand is controlled with service levels. Numerical studies compare the solution methods and give managerial implications in presence of stochastic production output. This book addresses practitioners, consultants, and developers as well as students, lecturers, and researchers with focus on lot sizing, production planning, and supply chain management.

Dynamic lot sizing problems with stochastic production output

Dynamic lot sizing problems with stochastic production output PDF Author: Michael Kirste
Publisher: BoD – Books on Demand
ISBN: 3744838056
Category : Business & Economics
Languages : en
Pages : 250

Get Book Here

Book Description
In the real world, production systems are affected by external and internal uncertainties. Stochastic demand - an external uncertainty - arises mainly due to forecast errors and unknown behavior of customers in future. Internal uncertainties occur in situations where random yield, random production capacity, or stochastic processing times affect the productivity of a manufacturing system. The resulting stochastic production output is especially present in industries with modern and complex technologies as the semiconductor industry. This thesis provides model formulations and solution methods for capacitated dynamic lot sizing problems with stochastic demand and stochastic production output that can be used by practitioners within Manufacturing Resource Planning Systems (MRP), Capacitated Production Planning Systems (CPPS), and Advanced Planning Systems (APS). In all models, backordered demand is controlled with service levels. Numerical studies compare the solution methods and give managerial implications in presence of stochastic production output. This book addresses practitioners, consultants, and developers as well as students, lecturers, and researchers with focus on lot sizing, production planning, and supply chain management.

Stochastic Dynamic Lot-Sizing in Supply Chains

Stochastic Dynamic Lot-Sizing in Supply Chains PDF Author: Timo Jannis Hilger
Publisher: BoD – Books on Demand
ISBN: 3738626972
Category : Business & Economics
Languages : en
Pages : 230

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Book Description
Companies frequently operate in an uncertain environment and many real life production planning problems imply volatility and stochastics of the customer demands. Thereby, the determination of the lot-sizes and the production periods significantly affects the profitability of a manufacturing company and the service offered to the customers. This thesis provides practice-oriented formulations and variants of dynamic lot-sizing problems in presence of restricted production resources and demand uncertainty. The demand fulfillment is regulated by service level constraints. Additionally, integrated production and remanufacturing planning under demand and return uncertainty in closed-loop supply chains is addressed. This book offers introductions to these problems and presents approximation models that can be applied under uncertainty. Comprehensive numerical studies provide managerial implications. The book is written for practitioners interested in supply chain management and production as well as for lecturers and students in business studies with a focus on supply chain management and operations management.

Inventory Analytics

Inventory Analytics PDF Author: Horst Tempelmeier
Publisher: BoD – Books on Demand
ISBN: 375193071X
Category : Business & Economics
Languages : en
Pages : 290

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Book Description
This textbook provides a practice-oriented introduction into Analytics-based inventory management in complex supply chains. In the context of Business Analytics, we concentrate on Prescriptive Analytics. In addition to standard single-level inventory models also multi-level approaches for the optimal allocation of safety inventory are presented. Moreover, dynamic lot sizing problems under random demand and random yield and their relationship to Material Requirements Planning (MRP) are discussed.The models and algorithms are illustrated with the help of numerous examples. The book has been written for students of Supply Chain Management and Operations Management as well as for practitioners who are confronted with inventory management in their daily work.

An Improved Algorithm for Dynamic Lot Sizing Problem with Learning Effect in Setups

An Improved Algorithm for Dynamic Lot Sizing Problem with Learning Effect in Setups PDF Author: Kavindra Malik
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 16

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Book Description


Optimality of Myopic Policies for Dynamic Lot-Sizing Problems in Serial Production Lines with Random Yields and Autoregressive Demand

Optimality of Myopic Policies for Dynamic Lot-Sizing Problems in Serial Production Lines with Random Yields and Autoregressive Demand PDF Author: Matthew J. Sobel
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
We study lot-size policies in a serial, multi-stage, manufacturing/inventory system with two key generalizations, namely (1) random yields at each production stage and (2) an autoregressive demand process. Previous research shows that the optimal policies in models with random yields (even in models with a single installation) lack the familiar order-up-to structure and are not myopic. Thus, dynamic programming algorithms are needed to compute optimal policies and one encounters the “curse of dimensionality;” this is exacerbated here by the need to expand the size and dimension of the state space to accommodate the autoregressive demand feature. Nevertheless, although our model is more complex, we prove that there is an optimal policy with the order-up-to feature and, more importantly, that the optimal policy is myopic. This avoids the computational burden of dynamic programming. Our results depend on two assumptions concerning the stochastic yield, namely that the expected yield at a work station is proportional to the lot size, and the distribution of the deviation of the yield from its mean does not depend on the lot size. We introduce the concept of echelon-like variables to derive the structure of optimal policies; this is a generalization of the echelon variables in Clark and Scarf (1960). Furthermore, we show that the same kind of policy is optimal for several criteria: infinite-horizon discounted cost, infinite-horizon long-run average cost, and finite-horizon discounted cost (with the appropriate choice of the salvage value function).

Multi-Level Lot Sizing and Scheduling

Multi-Level Lot Sizing and Scheduling PDF Author: Alf Kimms
Publisher: Springer Science & Business Media
ISBN: 3642501621
Category : Business & Economics
Languages : en
Pages : 367

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Book Description
This book is the outcome of my research in the field of multi levellot sizing and scheduling which started in May 1993 at the Christian-Albrechts-University of Kiel (Germany). During this time I discovered more and more interesting aspects ab out this subject and I had to learn that not every promising idea can be thoroughly evaluated by one person alone. Nevertheless, I am now in the position to present some results which are supposed to be useful for future endeavors. Since April 1995 the work was done with partial support from the research project no. Dr 170/4-1 from the "Deutsche For schungsgemeinschaft" (D FG). The remaining space in this preface shaH be dedicated to those who gave me valuable support: First, let me express my deep gratitude towards my thesis ad visor Prof. Dr. Andreas Drexl. He certainly is a very outstanding advisor. Without his steady suggestions, this work would not have come that far. Despite his scarce time capacities, he never rejected proof-reading draft versions of working papers, and he was always willing to discuss new ideas - the good as weH as the bad ones. He and Prof. Dr. Gerd Hansen refereed this thesis. I am in debted to both for their assessment. I am also owing something to Dr. Knut Haase. Since we al most never had the same opinion when discussing certain lot sizing aspects, his comments and criticism gave stimulating input.

Production Strategies for a Stochastic Lot-sizing Problem Using Overtime

Production Strategies for a Stochastic Lot-sizing Problem Using Overtime PDF Author: N. P. Dellaert
Publisher:
ISBN:
Category :
Languages : en
Pages : 25

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Book Description


Heuristics for the Stochastic Capacitated Lot Sizing Problem

Heuristics for the Stochastic Capacitated Lot Sizing Problem PDF Author: Isaac Chemmanam
Publisher:
ISBN:
Category : Dynamics
Languages : en
Pages : 208

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Book Description


Innovative Quick Response Programs in Logistics and Supply Chain Management

Innovative Quick Response Programs in Logistics and Supply Chain Management PDF Author: T. C. Edwin Cheng
Publisher: Springer Science & Business Media
ISBN: 3642043135
Category : Business & Economics
Languages : en
Pages : 470

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Book Description
Quick Response (QR) policy is a market-driven business strategy in which supply chain members work together to react quickly to volatile market demand. Nowadays, with advances in information technologies (such as RFID and ERP systems), new challenges and opportunities arise for the application of QR. This handbook explores QR extensively with a view to discovering innovative QR measures that can help tackle the observed and emerging challenges. The book is organized into four parts, which include chapters on analytical modeling and analyses, information technologies, cases, reviews, and applications. This handbook provides new analytical and empirical results with valuable insights, which will not only help supply chain agents to better understand the latest applications of QR in business, but also help practitioners and researchers to know how to improve the effectiveness of QR using innovative methods.

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems PDF Author: Alexandre Dolgui
Publisher: Springer Nature
ISBN: 303085874X
Category : Computers
Languages : en
Pages : 779

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Book Description
The five-volume set IFIP AICT 630, 631, 632, 633, and 634 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2021, held in Nantes, France, in September 2021.* The 378 papers presented were carefully reviewed and selected from 529 submissions. They discuss artificial intelligence techniques, decision aid and new and renewed paradigms for sustainable and resilient production systems at four-wall factory and value chain levels. The papers are organized in the following topical sections: Part I: artificial intelligence based optimization techniques for demand-driven manufacturing; hybrid approaches for production planning and scheduling; intelligent systems for manufacturing planning and control in the industry 4.0; learning and robust decision support systems for agile manufacturing environments; low-code and model-driven engineering for production system; meta-heuristics and optimization techniques for energy-oriented manufacturing systems; metaheuristics for production systems; modern analytics and new AI-based smart techniques for replenishment and production planning under uncertainty; system identification for manufacturing control applications; and the future of lean thinking and practice Part II: digital transformation of SME manufacturers: the crucial role of standard; digital transformations towards supply chain resiliency; engineering of smart-product-service-systems of the future; lean and Six Sigma in services healthcare; new trends and challenges in reconfigurable, flexible or agile production system; production management in food supply chains; and sustainability in production planning and lot-sizing Part III: autonomous robots in delivery logistics; digital transformation approaches in production management; finance-driven supply chain; gastronomic service system design; modern scheduling and applications in industry 4.0; recent advances in sustainable manufacturing; regular session: green production and circularity concepts; regular session: improvement models and methods for green and innovative systems; regular session: supply chain and routing management; regular session: robotics and human aspects; regular session: classification and data management methods; smart supply chain and production in society 5.0 era; and supply chain risk management under coronavirus Part IV: AI for resilience in global supply chain networks in the context of pandemic disruptions; blockchain in the operations and supply chain management; data-based services as key enablers for smart products, manufacturing and assembly; data-driven methods for supply chain optimization; digital twins based on systems engineering and semantic modeling; digital twins in companies first developments and future challenges; human-centered artificial intelligence in smart manufacturing for the operator 4.0; operations management in engineer-to-order manufacturing; product and asset life cycle management for smart and sustainable manufacturing systems; robotics technologies for control, smart manufacturing and logistics; serious games analytics: improving games and learning support; smart and sustainable production and supply chains; smart methods and techniques for sustainable supply chain management; the new digital lean manufacturing paradigm; and the role of emerging technologies in disaster relief operations: lessons from COVID-19 Part V: data-driven platforms and applications in production and logistics: digital twins and AI for sustainability; regular session: new approaches for routing problem solving; regular session: improvement of design and operation of manufacturing systems; regular session: crossdock and transportation issues; regular session: maintenance improvement and lifecycle management; regular session: additive manufacturing and mass customization; regular session: frameworks and conceptual modelling for systems and services efficiency; regular session: optimization of production and transportation systems; regular session: optimization of supply chain agility and reconfigurability; regular session: advanced modelling approaches; regular session: simulation and optimization of systems performances; regular session: AI-based approaches for quality and performance improvement of production systems; and regular session: risk and performance management of supply chains *The conference was held online.